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研究生:彭柏
研究生(外文):Po Peng
論文名稱:感知無線電網路對於次要用戶採用緩衝器與頻譜租用之連結允入控制比較分析
論文名稱(外文):Comparison Analysis of Call Admission Control Schemes with Buffer and Spectrum Leasing for Secondary Users in Cognitive Radio Networks
指導教授:鍾順平
指導教授(外文):Shun-Ping Chung
口試委員:林永松王乃堅鍾順平
口試委員(外文):Yeong-Sung LinNai-Jian WangShun-Ping Chung
口試日期:2020-07-21
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:電機工程系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:229
中文關鍵詞:感知無線電網路連結允入控制佔先優先權頻譜租用緩衝器
外文關鍵詞:Cognitive radio networkcall admission controlpreemptive priorityspectrum leasingbuffer
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  • 被引用被引用:0
  • 點閱點閱:84
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摘要 I
Abstract II
Contents III
List of Tables V
List of Figures V
1.Introduction 1
2.System Model 3
2.1 CAC1 5
2.2 CAC2 6
2.3 CAC3 7
3.Analytical Model 11
3.1 CAC1 11
3.1.1 Balance Equations 11
3.1.2 Steady State Probability Distribution 18
3.1.3 Performance Measures 18
3.2 CAC2 21
3.2.1 Balance Equations 21
3.2.2 Steady State Probability Distribution 32
3.2.3 Performance Measures 32
3.3 CAC3 35
3.3.1 Balance Equations 37
3.3.2 Steady State Probability Distribution 77
3.3.3 Performance Measures 77
4. Simulation Model 144
4.1 CAC1 145
4.1.1 Main Program 145
4.1.2 Timing Subprogram 145
4.1.3 PU Arrival Subprogram 146
4.1.4 PU Departure Subprogram 146
4.1.5 SU Arrival Subprogram 147
4.1.6 SU Departure Subprogram 148
4.1.7 Buffer Drop Subprogram 148
4.1.8 Performance Measures 149
4.2 CAC2 152
4.2.1 Main Program 152
4.2.2 Timing Subprogram 152
4.2.3 PU Arrival Subprogram 153
4.2.4 PU Departure Subprogram 153
4.2.5 SU Arrival Subprogram 154
4.2.6 SU Departure Subprogram 155
4.2.7 Buffer Drop Subprogram 156
4.2.8 Performance Measures 156
4.3 CAC3 159
4.3.1 Main Program 159
4.3.2 Timing Subprogram 159
4.3.3 PU Arrival Subprogram 160
4.3.4 PU Departure Subprogram 161
4.3.5 SU Arrival Subprogram 162
4.3.6 SU Departure Subprogram 162
4.3.7 Buffer Drop Subprogram 164
4.3.8 Performance Measures 164
5. Numerical Results 182
5.1 PU Mean Arrival Rate 183
5.2 PU Mean Departure Rate 186
5.3 SU Mean Arrival Rate 190
5.4 SU Mean Departure Rate 193
5.5 Buffer Size 197
6. Conclusions 227
References 228
[1] M. A. McHenry, P. A. Tenhula, D. McCloskey, D. A. Roberson, and C. S. Hood, “Chicago Spectrum Occupancy Measurements & Analysis and a Long-term Studies Proposal,” TAPAS '06: Proceedings of the first international workshop on Technology and policy for accessing spectrum, DOI: 10.1145/1234388.1234389, Boston, USA, Aug. 2006.
[2] M. H. Islam, C. L. Koh, S. W. Oh, X. Qing, Y. Y. Lai, C. Wang, Y. C. Liang, B. E. Toh, F. Chin, G. L. Tan, and W. Toh, “Spectrum Survey in Singapore: Occupancy Measurements and Analyses,” 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), DOI: 10.1109/CROWNCOM.2008.4562457, pp. 1-7, Singapore, May 2008.
[3] M. Lopez-Benitez, A. Umbert, and F. Casadevall, “Evaluation of Spectrum Occupancy in Spain for Cognitive Radio Applications,” VTC Spring 2009 - IEEE 69th Vehicular Technology Conference, DOI: 10.1109/VETECS.2009.5073544, pp. 1-5, Barcelona, April 2009.
[4] N. Q. B. Vo, Q. C. Le, Q. P. Le, D. T. Tran, T. Q. Nguyen, and M. T. Lam, “Vietnam Spectrum Occupancy Measurements and Analysis for Cognitive Radio Applications,” The 2011 International Conference on Advanced Technologies for Communications (ATC 2011), DOI: 10.1109/ATC.2011.6027452, pp. 135-143, Sep. 2011.
[5] J. Mitola III and G. Q. Maguire Jr., “Cognitive Radio: Making Software Radios More Personal,” IEEE Personal Commun., vol. 6, no. 4, pp. 13-18, Aug. 1999.
[6] M. Sherman, A. N. Mody, R. Martinez, and C. Rodriguez, “IEEE Standards Supporting Cognitive Radio and Networks, Dynamic Spectrum Access, and Coexistence,” IEEE Commun. Mag., vol. 46, no. 7, pp. 72-79, July 2008.
[7] S. Bhandari and S. Joshi, “Cognitive Radio Technology in 5G Wireless Communications,” 2018 2nd IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES), DOI: 10.1109/ICPEICES.2018.8897345, Oct. 2018
[8] F. A. Awin, Y. M. Alginahi, E. Abdel-Raheem, and K. Tepe, “Technical Issues on Cognitive Radio-Based Internet of Things Systems: A Survey,” IEEE Access, DOI: 10.1109/ACCESS.2019.2929915, vol. 7, pp. 97887-97908, July 2019.
[9] Z. Ni, H. Shan, W. Shen, J. Wang, A. Huang, and X. Wang, “Dynamic Channel Allocation-based Call Admission Control in Cognitive Radio Networks,” 2013 International Conference on Wireless Communications and Signal Processing, DOI: 10.1109/WCSP.2013.6677288, pp. 1-6, Oct. 2013.
[10] S. Dey, T. Chakraborty, and I. S. Misra, “A Sub-band Based CAC Scheme Using Adaptive Codec Switching for Improved Capacity and GoS of Cognitive VoIP Users,” 2017 Fourth International Conference on Signal Processing, Communication and Networking (ICSCN), DOI: 10.1109/ICSCN.2017.8085715, Oct. 2017.
[11] I. A. M. Balapuwaduge, L. Jiao, V. Pla and F. Y. Li, “Channel Assembling with Priority-based Queues in Cognitive Radio Networks: Strategies and Performance Evaluation,” IEEE Trans. on Wireless Commun., DOI: 10.1109/TWC.2013.120713.121948, vol. 13, no. 2, pp. 630-645, Dec. 2013.
[12] I. A. M. Balapuwaduge, A. Rajanna, M. Kaveh and F. Y. Li, “Performance Evaluation of Three Dynamic Channel Access Strategies for Spectrum leasing in CRNs,” 2015 ICC, DOI: 10.1109/ICC.2015.7249537, pp. 7570-7575, London, U.K., June 8-12, 2015.
[13] J. Lee and J. So, “Analysis of Cognitive Radio Networks with Channel Aggregation,” IEEE WCNC, DOI: 10.1109/WCNC.2010.5506262, pp.1-6, Sydney, Australia, April 2010.
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